Travel time is a crucial variable both in traffic demand modeling and for measuring network performance. The objectives of this study focused on developing a methodology to characterize arterial travel time patterns by travel
time distributions, proposing methods for estimating such distributions from static information and refining them with the use of historical GPS probe information, and given such time and location-based distribution, using realtime GPS probe information to produce accurate path travel times as well as monitor arterial traffic conditions. This project set the foundations for a realistic use of GPS probe travel time information and presented the proposed methodologies through two comprehensive case studies. The first study used the Next Generation SIMulation (NGSIM) Peachtree Street dataset, and the second utilized both real GPS and simulation data of Washington Avenue, in Minneapolis, MN.